首页|四旋翼无人机滑模-CPCMAC联合控制半物理仿真系统

四旋翼无人机滑模-CPCMAC联合控制半物理仿真系统

扫码查看
原文链接
  • 万方数据
  • 维普
针对四旋翼无人机强耦合、欠驱动、非线性等特点，以及在实际飞行过程中极易受到干扰的问题，对四旋翼无人机动力学模型进行分析，提出了一种基于联合的四旋翼无人机姿态控制算法，并在此基础上设计了四旋翼无人机半物理仿真系统。首先，针对非线性系统设计滑模控制器，选择跟踪航迹和翻滚角设计位置控制率和姿态控制率。其次，滑模控制器在实际应用中易产生震荡，利用基于信用积分的小脑模型神经网络(CPCMAC)来学习滑模控制的方式。最后，搭建基于LabVIEW的控制站，同Matlab/Simulink进行数据收发控制。仿真结果表明，在跟踪目标相同时，提出的四旋翼无人机滑模-CPCMAC 联合控制相比于传统的比例积分微分(PID)控制和积分反步法控制优势明显，能够抑制超调和余差，在快速性和鲁棒性方面都更加优越。同时，构建的四旋翼无人机半物理仿真平台能清晰反馈出无人机参数的变化，应用预留的参数接口和地面控制站，降低了无人机飞控算法的开发难度，提高了开发效率，具有明显的实用价值。
A Semi-physical Simulation System with Sliding Mode-CPCMAC Joint Control for the Quad-rotor UAV
Aiming at the characteristics of strong coupling,underactuated,nonlinear and so on,and the problems of being easily interfered in the actual flight process of the quad-rotor Unmanned Aerial Vehicle(UAV),the dynamics model of the quad-rotor UAV was analyzed,and an attitude control algorithm of the quad-rotor UAV based on sliding mode-Credit Points Cerebellar Model Articulation Controller(CPCMAC)was proposed.On this basis,the semi-physical simulation system of the quad-rotor UAV was designed.Firstly,the sliding mode controller is designed for the nonlinear system,with position control rate and attitude control rate tailored to tracking track and roll angle.Secondly,as practical application of sliding mode controller can produce oscillation,a cerebellar neural network based on credit integral is employed to learn the sliding mode control.Finally,a LabVIEW-based control station is established for data transmission and transmission control with Matlab/Simulink.Simulation results demonstrate that compared with traditional Proportional Integral Derivative(PID)control and integral backstepping method control,proposed sliding mode-CPCMAC joint controll for the quad-rotor UAV has significant advantages in suppressing overshoot and residual while being superior in rapidity and robustness.Meanwhile,built quad-rotor UAV semi-physical simulation platform provides clear feedback on changes of UAV parameters;reserved parameter interface application along with ground control station reduces development difficulty of UAV flight-control algorithm thereby improving development efficiency having obvious practical value.

unmanned aerial vehiclecerebellar model articulation controllersliding mode controlsemi-physical simulationwind field

黄鹤、谢飞宇、杨澜、王会峰、高涛

展开 >

长安大学 西安市智慧高速公路信息融合与控制重点实验室,陕西 西安 710064

长安大学 电子与控制工程学院,陕西 西安 710064

无人机 小脑模型神经网络 滑模控制 半物理仿真 风场

国家重点研发计划国家自然科学基金面上项目国家自然科学基金面上项目陕西省重点研发计划西安市智慧高速公路信息融合与控制重点实验室(长安大学)开放基金中央高校基本科研业务费资助项目

2021 YFB250120052172324521723792024GX-YBXM-288300102323502300102323501

2024

复旦学报(自然科学版)
复旦大学

复旦学报(自然科学版)

CSTPCD北大核心
影响因子：0.388
ISSN：0427-7104
年,卷(期)：2024.63(1)
  • 10